Are there L1 skill and L2 aptitude differences between high- and low-achieving L2 learners?

Are there L2 achievement and proficiency differences among individuals who differ in L1 skills and L2 aptitude?

Because research with U.S. L2 learners has found strong relationships among students’ L1 skills, L2 aptitude, and L2 proficiency and achievement, answers to the first two questions are reviewed in this section.

By 2001, L2 researchers had proposed a number of hypotheses to explain IDs in L2 learning and achievement. Some researchers maintained that variables such as attitude/motivation (Gardner, Reference Gardner1985), anxiety (Horwitz, Horwitz, & Cope, Reference Horwitz, Horwitz and Cope1986), and failure to use language learning strategies (Oxford, Reference Oxford, Parry and Stansfield1990) were causal factors in L2 learning differences. Other researchers focused on language-related variables and developed prognostic (aptitude) tests designed to predict one’s level of L1 achievement and proficiency. In particular, John Carroll paved the way for a major breakthrough in thinking about aptitude for L2 learning with the development of the MLAT (Carroll & Sapon, 1959, 2001), which identified four factors – phonetic coding, grammatical sensitivity, rote memorization ability, and inductive language learning ability – each of which measured distinct language skills. Carroll’s Model of School Learning (Carroll, Reference Carroll1963) recognized factors besides language aptitude thought to be necessary for successful L2 learning. Factors within the individual included aptitude (amount of time needed), ability to understand instruction, and perseverance, while factors in external conditions included opportunity (time allowed for learning, quality of instruction). Carroll’s model recognized that language aptitude (as measured by the MLAT) was necessary but not sufficient to attain L2 proficiency.

Starting in the 1990s, L1 educators Sparks and Ganschow, both of whom were learning disability (LD) and reading disability (dyslexia) specialists in the U.S.A., linked research on L1 learning and reading problems to research on L2 learning differences. Because of increased enrollments in U.S. secondary and postsecondary institutions starting in the 1960s, both L1 and L2 educators recognized that larger numbers of students were experiencing L2 learning problems. After introducing the LCDH in 1989, Sparks and Ganschow began a series of studies in the 1990s which found that high- and low-achieving L2 learners exhibited significant differences in L1 reading, spelling, and grammar skills and in L2 aptitude (MLAT) (Ganschow et al., Reference Ganschow, Sparks, Javorsky, Pohlman and Bishop-Marbury1991, Reference Sparks, Ganschow, Javorsky, Pohlman and Patton1992; Sparks et al., Reference Sparks, Ganschow, Fluharty and Little1996). Figure 11.1 depicts the scores of the high- and low-achieving groups on measures of L1 skills and L2 aptitude in studies conducted by Sparks, Ganschow, and colleagues. Other researchers had provided support for the finding of L1 differences between stronger and weaker L2 learners (e.g., see Dufva & Voeten, Reference Dufva and Voeten1999; Hulstijn & Bossers, Reference Hulstijn and Bossers1992; Humes-Bartlo, Reference Humes-Bartlo, Hyltenstam and Obler1989), particularly in L1 phonological (speech sounds) and phonological/orthographic (sound–symbol) skills (Kohonen, Reference Kohonen1995; Papagno, Valentine, & Baddeley, Reference Papagno, Valentine and Baddeley1991).

Figure 11.1 Continuum of scores on L1 skills and L2 aptitude measures for the high- and low-achieving L2 learners

Since 2001, Sparks and his colleagues have conducted a number of studies investigating the question of differences between high-achieving and low-achieving L2 learners, some of which are described in this section and subsequent sections. In a longitudinal study conducted over 10 years, they followed students from the beginning of 1st grade through the end of 10th grade, when two years of L2 study had been completed in 9th and 10th grades (Sparks, Patton, Ganschow, & Humbach, Reference Sparks, Patton, Ganschow and Humbach2009). The participants were administered several measures of L1 skills in elementary school, the MLAT in 9th grade, and, at the end of 10th grade, L2 proficiency tests that measured word decoding, reading comprehension, spelling, writing, oral language, and listening comprehension (Spanish, French, German). They were then divided into high, average, and low proficiency groups according to their scores on the L2 proficiency measure. Results revealed overall group differences on the L1 skill measures, the MLAT, and in L2 word decoding and spelling. Between-group comparisons showed that the high proficiency L2 learners exhibited stronger L1 skills than the average and low proficiency learners as early as 2nd grade. In another study with these participants, the authors administered L1 print exposure (reading volume) measures, divided the participants into high, average, and low print exposure groups, and compared them on the L1 skill, L2 aptitude, and L2 proficiency measures (Sparks et al., Reference Sparks, Patton and Ganschow2012). After controlling for IQ, findings showed that participants with a higher volume of L1 print exposure also displayed stronger L1 skills that emerged as early as 1st grade, higher L2 aptitude, and stronger oral and written L2 proficiency. The results of these studies, and others, confirmed that students with stronger L1 skills also exhibit higher L2 aptitude and achieve higher levels of L2 proficiency. Figure 11.2 depicts the scores of the high, average, and low proficiency groups on measures of L1 skills and L2 aptitude in studies conducted by Sparks, Ganschow, and colleagues.

Figure 11.2 Continuum of scores on L1 skills and L2 aptitude measures for the high, average, and low L2 proficiency groups

In a retrospective study, Sparks, Patton, and Ganschow (Reference Sparks, Patton and Ganschow2012) examined the L1 skills measured prior to enrolling in L2 courses, MLAT scores, and L2 proficiency profiles of 208 students who had completed two years of secondary-level L2 courses. A cluster analysis (k-means method) was performed to determine whether distinct cognitive and achievement profiles of more and less successful L2 learners would emerge. The results revealed three distinct profiles in which the high-achieving cluster scored in the above average range on most L1 and L2 measures; the average-achieving cluster scored in the average range; and the low-achieving cluster scored in the low average and below average range on most measures. Figure 11.3 depicts the scores of the three clusters on the L1 and L2 measures. The findings suggest that students’ levels of L1 skills developed prior to L2 exposure are strongly related to and consistent with their subsequent L2 aptitude and L2 proficiency, and that students’ L2 attainment is moderated by their level of L1 ability. In another longitudinal study over three years, high-, average-, and low-achieving U.S. L2 learners exhibited significant differences in L1 achievement skills, L1 cognitive processing skills (e.g., working memory), L1 print exposure, and L2 aptitude (MLAT) at the end of first-, second-, and third-year Spanish courses (Sparks, Patton, & Luebbers, Reference Sparks, Patton and Luebbers2019a). On all measures, the high-achieving group achieved significantly stronger scores than the average and low groups. The results suggested that IDs in L2 achievement reflect IDs in L1 skills; for example, students with higher achievement in L1 reading and spelling also attained higher achievement in L2 reading and spelling.

Figure 11.3 Scores $\left(M=\mathbf{100},\mathit{SD}=\mathbf{15}\right)$ of the high (c1), average (c2), and low (c3) clusters on the MLAT, IQ, L1 skills, and L2 proficiency measures

Sparks et al. have conducted a long line of research studies with U.S. learners classified as LD enrolled in L2 courses (e.g., see Ganschow & Sparks; Sparks, Reference Sparks2001, Reference Sparks2016). Given space constraints, that research is not reviewed here. However, this evidence has found that: a) there are no L1 skills, cognitive ability, and L2 aptitude differences between LD students and low-achieving (non-LD) students in L2 classes; and b) there is no evidence for an L2 “disability.” Instead, like L1 learning, L2 achievement runs along a continuum of very good to very poor L2 learners, with no evidence for a “cut point” below which an individual can be classified as “disabled” in L2.

What Are the Best Predictors of L2 Proficiency and Achievement?

In the 1960s and 1970s, studies revealed that language aptitude, as embodied in the MLAT, was a strong predictor of success in L2 learning. These findings had shown that: a) people vary in their language aptitude, b) variation in aptitude has considerable significance for language learning success, c) people with the same overall aptitude may exhibit differences in language component abilities (phonetic coding, grammar, memory), and d) IDs in L2 learning components have connections to L1 learning components (Skehan, Reference Skehan1989). However, Skehan (Reference Humes-Bartlo, Hyltenstam and Obler1989) reported that the language aptitude concept had fallen out of favor with L2 researchers. With the movement away from language aptitude testing, there was an increasing emphasis on variables such as motivation, language learning strategies, and other affective variables (e.g., language anxiety) thought to be important for L2 proficiency. Dörnyei and Skehan (Reference Dörnyei, Skehan, Doughty and Long2003) summarized research showing that IDs in learners’ language aptitude and motivation have been found to be consistently strong predictors of L2 achievement.

Prior to 2001, Sparks et al. conducted prediction studies with secondary-level U.S. L2 learners in which their L1 skill and L2 aptitude scores (on the MLAT) were used as predictor variables for L2 proficiency. In one study with 154 participants, they found that the best predictors of L2 course grades were students’ scores on the MLAT, their 8th grade English grade, and a measure of L1 spelling (Sparks, Ganschow, & Patton, Reference Sparks, Ganschow and Patton1995). In the second study, they followed the students through a second year of L2 courses and found that the best predictors of L2 proficiency were L1 vocabulary, L2 word decoding, and first-year L2 course grades (Sparks, Ganschow, Patton et al., Reference Sparks, Ganschow, Artzer, Siebenhar and Plageman1997). A factor analysis study with the test battery used in the two aforementioned studies yielded three factors: Verbal Memory (MLAT subtests I and V, L1 vocabulary), Phonological Coding/Recoding (L1 reading, L1 spelling, MLAT subtest II), and Cognitive Speed (timed measures of L1 skills and MLAT subtests III and IV) (Sparks et al., Reference Sparks, Javorsky, Patton and Ganschow1998). Multiple regression analyses using the three factors as predictor variables showed that all three factors were significant in predicting L2 proficiency.

Since 2001, Sparks and colleagues have conducted several investigations using L1 skill and L2 aptitude variables to predict L2 proficiency and achievement. In the 10-year longitudinal investigation cited earlier, L1 literacy skills in elementary school were strong predictors of L2 aptitude (MLAT) measured several years later, and L2 literacy (reading, spelling) skills in primary school were the best predictors of L2 proficiency in secondary school (Sparks et al., Reference Sparks, Patton, Ganschow, Humbach and Javorsky2006). In another study with these participants, L1 word decoding and spelling skills in elementary school were found to be the best predictor of L2 word decoding and spelling skills in high school (Sparks et al., Reference Sparks, Patton, Ganschow, Humbach and Javorsky2008). In yet another study with these participants, results revealed that L1 reading achievement in 10th grade made significant and unique contributions to L2 reading, L2 listening comprehension, and L2 oral proficiency after adjusting for the effects of early L1 literacy skills, cognitive ability, and L2 aptitude (Sparks, Patton, Ganschow, & Humbach, Reference Sparks, Patton, Ganschow and Humbach2009). Subsequent analyses showed that an environmental variable, L1 print exposure (reading volume), made unique contributions to L2 reading, L2 word decoding, L2 writing, L2 listening/speaking, and overall L2 proficiency even after controlling for the effects of L1 literacy in elementary school, cognitive ability, and L2 aptitude. In two similar studies with Hebrew-speaking elementary school students learning English, Kahn-Horwitz, Shimron, and Sparks (Reference Proctor, Carla, August and Snow2005, Reference Sparks2006) found that skills in L1 phonological awareness, L1 word decoding, and L1 vocabulary predicted L2 (English) reading skills and discriminated between strong and weak readers among learners of English as a foreign language.

Sparks et al. also conducted two prediction studies in which a factor analysis of a test battery that included L1 skills measured in primary school, cognitive ability, L2 aptitude (MLAT), and L2 affective measures (motivation, anxiety) was employed to predict oral and written L2 proficiency in secondary school (Sparks et al., Reference Sparks, Patton, Ganschow and Humbach2011). The analysis yielded four factors: Language Analysis (L1/L2 language comprehension, grammar, vocabulary), Phonology/Orthography (L1/L2 phonetic coding and phonological processing), IQ/Memory (L1 cognitive ability, L2 paired associate learning), and Self-Perception of Language Skills (L2 motivation, L2 anxiety). Multiple regression analyses showed that the four factors explained 76% of the variance in oral and written L2 proficiency. In a more recent study with a different set of participants, principal components analysis of a different test battery yielded three factors: Phonological and Orthographic Coding/Working Memory (L1 word decoding, L2 phoneme awareness, L1 working memory, L1 phonological memory), Language Analysis (L1 reading comprehension, L2 metacognitive knowledge, L1 writing, L2 vocabulary), and L2 Aptitude (all five MLAT subtests) (Sparks, Patton, & Luebbers, Reference Sparks, Patton, Luebbers, Wen, Skehan, Biedroń, Li and Sparks2019b). Multiple regression analyses with the three factors as predictor variables for L2 proficiency revealed that the Phonological and Orthographic Coding/Working Memory factor predicted the largest amount of variance in L2 word decoding and L2 spelling; the Language Analysis and L2 Aptitude factors predicted the largest amount of variance in L2 reading comprehension, L2 vocabulary, L2 writing, and L2 listening comprehension. These factor analysis studies suggested that L2 learning and L2 aptitude are componential, that is, efficient functioning of different L2 skills relies on different components of language. For example, L2 word decoding and L2 spelling rely primarily on the ability to learn and use letter–sound relationships, while L2 language comprehension, vocabulary, and writing rely primarily on the ability to analyze language and oral language comprehension.

In a recent longitudinal study, U.S. secondary students were administered measures of L1 written/oral achievement, L1 cognitive processing, and L2 aptitude. They were then followed over three years of learning Spanish and administered standardized measures of L2 literacy and oral proficiency at the end of each year (Sparks et al.,). Hierarchical regressions showed that IDs in L1 achievement in press alone (reading, writing, vocabulary, print exposure) accounted for substantial unique variance in L2 reading, writing, listening comprehension, and oral proficiency, while L2 aptitude accounted for additional unique variance at the end of each year. A new finding showed that variance explained by L1 skills for predicting L2 achievement increased from first to second to third year. The results lend additional support to the conclusion of strong L1–L2 connections and important relationships between IDs in L1 ability and L2 achievement.

The findings that L1 skills are important predictors of L2 proficiency provide support for the study of L1–L2 relationships, leading to the question of why the MLAT has been found to be an important predictor of L2 proficiency, even in the presence of L1 skills. In a previous paper, Sparks et al. speculated that L2 aptitude tests such as the MLAT preempt (cut out) the variance in L2 proficiency that might be explained by L1 skills (Sparks, Patton, Ganschow, & Humbach, Reference Sparks, Patton, Ganschow and Humbach2009). They cited Skehan and Ducroquet (Reference Skehan and Ducroquet1988), who followed children from age three years to 13–14 years and found that early L1 development prior to entering school was strongly correlated with L2 aptitude and L2 achievement many years later; even so, students’ performance on the L2 aptitude tests was a stronger predictor of L2 achievement than their early L1 skills. Likewise, in Sparks et al.’s studies, there have been strong relationships between L1 achievement skills in elementary school and L2 proficiency several years later, but L2 aptitude was a strong predictor of L2 proficiency even in the presence of L1 skills. A simple explanation for the superiority of the MLAT over L1 achievement for predicting L2 achievement is that L2 aptitude tests comprise basic language tasks that measure the skills necessary for language learning generally, whether in L1 or L2. For example, the MLAT Phonetic Coding subtest measures a student’s phonological/orthographic ability (sound–symbol learning), the same skill that is measured by L1 word decoding and spelling measures. In a new paper, Sparks and Dale (Reference Sparks and Dale2022) found that the prediction from MLAT to L2 achievement is significantly and substantially due to variance in the L1 abilities captured by the MLAT. A more complex explanation may be that the MLAT measures an “underlying language learning capacity which is similar in first and foreign language learning settings” and has “the capacity to function as a measure of the ability to learn from decontextualized material” (Skehan, Reference Skehan1989, p. 34). In effect, L2 aptitude tests may draw their predictive value from tapping into students’ metalinguistic skills (their ability to explicitly think about, reflect on, and manipulate language) and the view that language analytic ability and metalinguistic ability are “two sides of the same coin” (Ranta, Reference Ranta and Robinson2002, p. 163). Thus, L2 aptitude may be, at least in part, a proxy for students’ L1 language analytic abilities and their metalinguistic skills (Sparks, 2022a, b).

Are There L1 Achievement and L2 Aptitude Differences in Individuals with Differing Levels of Language Anxiety?

Affective explanations for more or less successful L2 learners have always held a special place among L2 educators. In particular, motivation for L2 learning is thought to play an important role in L2 proficiency (MacIntyre & Gardner, Reference MacIntyre and Gardner1991). L2 educators have also hypothesized that a special type of anxiety for language learning might be a causal factor in failure to master an L2. Horwitz, Horwitz, and Cope (Reference Horwitz, Horwitz and Cope1986) developed the Foreign Language Classroom Anxiety Scale (FLCAS) to survey the degree of anxiety for L2 learning. Research with the FLCAS found a negative relationship between anxiety and L2 course grades and L2 achievement (see reviews by Horwitz, Reference Horwitz2010; Trang, Reference Trang2012). Several years later, Horwitz and colleagues introduced the Foreign Language Classroom Reading Anxiety Scale (FLRAS) into the L2 literature (Saito, Garza, & Horwitz, Reference Saito, Garza and Horwitz1999). Like the FLCAS, they found negative correlations between L2 reading anxiety and L2 reading skills.

Early on, Sparks and Ganschow (Reference Sparks and Ganschow1991) investigated the L1 anxiety construct and raised the question of whether language anxiety is a cause or consequence of IDs in L2 aptitude and L2 achievement. They reported that the 33 items on the FLCAS were related to an individual’s speed of language processing, receptive and expressive language skills, and verbal memory (i.e., the items were language related) and proposed that L1 skills and L2 aptitude would be confounding variables when considering the role of anxiety for L2 learning. They also noted that students’ responses on the FLCAS may indirectly measure their language ability and/or reflect their self-perceptions of their language learning skills, not anxiety for language learning.

Prior to 2001, Sparks and Ganschow used Horwitz’s FLCAS to determine whether there would be language skill differences among university L2 learners classified as high, average, and low anxiety according to their responses on the FLCAS (Ganschow et al., Reference Ganschow, Sparks and Anderson1994). Their findings showed overall differences among the three groups in L1 skills and L2 aptitude (MLAT), and between-group differences in L1 skills and L2 aptitude favoring the low and average anxious groups. They replicated this study with high school L2 learners studying Spanish, French, and German and found similar results (Ganschow & Sparks, Reference Ganschow and Sparks1996). In a follow-up investigation with these high school L2 learners after two years of L2 courses, they found significant differences in the students’ oral and written L2 proficiency favoring the average and low anxious learners (Sparks, Ganschow, Artzer, et al., Reference Sparks, Ganschow, Artzer, Siebenhar and Plageman1997). These findings supported the hypothesis that language ability may be a confounding variable in affective explanations for L2 learning outcomes.

Since 2001, Sparks et al. have continued to study the L2 anxiety hypothesis. In one study, U.S. students were followed over 10 years (Sparks & Ganschow, Reference Sparks and Ganschow2007). Their L1 skills were measured in 1st–5th grades, the MLAT and the FLCAS were administered in 9th grade, and L2 oral and written proficiency measures were administered in 10th grade after two years of L2 courses. The students were divided into three groups – high, average, and low anxious – based on their FLCAS score and compared on the L1 and L2 measures. The findings showed that the low anxious group scored significantly higher than the high anxious group on the L1 skill measures as early as 2nd grade, the MLAT in 9th grade, and all L2 proficiency tests in 10th grade. Findings also revealed that the FLCAS administered in high school was negatively correlated with L1 measures of reading, spelling, and vocabulary as early as 1st grade. Sparks et al. noted that there was no a priori reason that students in 1st grade should be anxious about L2 learning several years before they encountered the L2 in 9th grade. The results suggested that the FLCAS is likely to be measuring students’ L1 ability, their (accurate) self-perceptions of their language learning skills, or both, and also that language ability and language (L2) aptitude are confounding variables in L2 anxiety research.

In another study, Sparks and Patton (Reference Sparks and Patton2013) conducted a path analysis and hierarchical regressions with the aforementioned dataset followed from 1st to 10th grades. The results of this investigation showed that the FLCAS accounted for significant unique variance in L1 skills in early elementary school several years before the students began L2 courses in 9th grade, and significant unique variance on the MLAT and L1 reading skills measured in 10th grade. Hierarchical regressions found that the FLCAS also predicted growth in L1 skills (reading, spelling, language) in elementary school from 1st to 5th grades and from elementary to high school (5th–10th grades). Here again, the authors suggested that there was no a priori reason that a survey purporting to tap language anxiety should predict unique variance and growth in L1 skills in elementary school and from middle school to high school many years before L2 courses, or that it should predict variance on an L2 aptitude test. The results suggested that the FLCAS is likely to be measuring IDs in students’ language skills and self-perceptions about their language learning ability, rather than a “special” anxiety unique to L2 learning.

Sparks et al. have also criticized the FLRAS (Saito, Garza, & Horwitz, Reference Saito, Garza and Horwitz1999) for the same reason as they criticized the FLCAS: The items are all related to an individual’s reading ability (Sparks, Ganschow, & Javorsky, Reference Sparks, Ganschow and Javorsky2000). In two recent studies with U.S. students followed over three years of L2 (Spanish) courses, the FLRAS (reading anxiety) and measures of L1 skills, L1 working and phonological memory, L1 print exposure and L1 reading attitudes, L1 metacognitive ability, MLAT, and L2 achievement (Spanish reading, spelling, vocabulary, writing, listening comprehension) were administered to the participants. In the first study (Sparks, Patton, & Luebbers, Reference Sparks, Patton and Luebbers2018a), the results showed that the FLRAS explained significant unique variance in most L1 skills and in L2 aptitude. Hierarchical regression analyses revealed that the FLRAS explained growth in L2 achievement from first- to second- to third-year Spanish courses. In the second study (Sparks et al., Reference Sparks, Luebbers, Castenada and Patton2018), the 266 participants were divided into three groups – low, average, and high anxious – and compared on the aforementioned L1 and L2 measures. Similar to studies with the FLCAS, the low anxiety group (on the FLRAS) scored significantly higher than the high anxiety group on all L1 measures, the MLAT, and the L2 achievement tests and scored significantly higher than the average anxiety group on most measures. The results also found negative correlations between the FLRAS and all L1 measures administered prior to the beginning of L2 courses. Like the FLCAS, Sparks et al. concluded that the FLRAS is also measuring IDs in students’ L1 skills, including cognitive processing (working memory), and L2 aptitude, not a special anxiety for language learning. Figure 11.4 depicts the scores of the high, average, and low anxiety groups on measures of L1 skills, L2 aptitude, and L2 proficiency in studies conducted by Sparks, Ganschow, and colleagues (see also Sparks & Alamer, 2022).

Figure 11.4 Continuum of scores on L1 skills, L2 aptitude, and L2 proficiency measures for the high, average, and low anxious groups

Sparks (Reference Sparks1995) outlined several ways in which L2 anxiety researchers could provide empirical support for their conjecture that anxiety is a causal factor in L2 learning, the most prominent of which was to measure and control for the obvious confounding variables – L1 skills and L2 aptitude. To the author’s knowledge of the studies, no researchers have followed this recommendation. L2 educators still contend that language anxiety “can impede the learning of the target language and hinder academic success; lead learners to abandon their studies; … sow the seeds of self-doubt … feelings of incompetence and degree of self-esteem” and create a host of other negative outcomes (Gkonou, Daubney, & Dawaele, Reference Gkonou, Daubney and Dawaele2017, p. 1). However, the results of investigations with L2 anxiety instruments and L1/L2 skills suggest that seeds of self-doubt, feelings of incompetence, low self-esteem, and anxiety itself are likely to come from a student’s lower levels of L1 ability and language aptitude, not anxiety.

Is There Long-Term, Cross-Linguistic Transfer from L1 to L2 Skills?

L2 researchers and educators have long suspected a relationship between L1 and L2 learning (Safa, Reference Safa2018), particularly for reading and spelling alphabetic languages (Geva & Verhoeven, Reference Geva and Verhoeven2000). Cross-linguistic transfer is the idea that language proficiency underlying cognitively demanding tasks, such as literacy and academic learning, is generally shared across languages. Once proficiency in one language is acquired, the cognitive components in L1 promote language and literacy development in L2. For reading, Seidenberg (Reference Seidenberg2013) and others have postulated that some aspects of reading are “universal (because people’s brain are essentially alike) and some are not (because of differences among writing systems and the languages they represent)” (p. 331) (see also Verhoeven & Perfetti, Reference Verhoeven and Perfetti2017, pp. 457–458). Numerous studies have found moderate to strong correlations between L1 and L2 word decoding and phonological awareness, and small to moderate correlations between L1 and L2 oral language skills (e.g., see Genesee et al., Reference Genesee, Geva, Dressler, Kamil, August and Shanahan2006; Melby-Lervåg & Lervåg, Reference Melby‐Lervåg and Lervåg2011).

In the U.S.A. and elsewhere, researchers have conducted studies with students learning to read English (ELLs) who have a wide variety of L1s with an eye toward cross-linguistic transfer (e.g., see Cárdenas-Hagan, Carlson, & Pollard-Durodola, Reference Cárdenas-Hagan, Carlson and Pollard-Durodola2007; Mancilla-Martinez & Lesaux, Reference Mancilla-Martinez and Lesaux2010; Shum et al., Reference Shum, Ho, Siegel and Au2016). However, to the author’s knowledge, no studies prior to 2001 had conducted systematic investigations that examined cross-linguistic transfer with U.S. students whose L1 is English and who were learning to read another language. As noted earlier, the great majority of U.S. students, all of whom are more or less proficient in English, begin L2 courses in secondary-level education. By 2001, Sparks et al. had established that there are strong relationships among U.S. students’ levels of L1 skills, L2 aptitude, and L2 achievement (course grades). However, with the time lag between learning to speak and read their L1 (1st grade) and starting L2 courses (9th grade), researchers had not examined the relationship between early L1 literacy skills and later L2 literacy and L2 oral language development.

Sparks et al. speculated that evidence for cross-linguistic transfer from L1 to L2 would provide support for the LCDH and claims that L1 skills serve as a foundation for L2 learning. To investigate the phenomenon of long-term, cross-linguistic transfer of L1–L2 skills in U.S. students, they conducted the longitudinal study over 10 years described earlier, in which they administered L1 literacy measures in 1st–5th grades, MLAT in 9th grade, and L2 proficiency and achievement tests at the end of 10th grade. In one study, Sparks, Patton, Ganschow, Humbach, & Javorsky (Reference Sparks, Patton, Ganschow, Humbach and Javorsky2009) divided the students who had completed two years of Spanish, French, or German into high, average, and low proficiency groups according to their L2 proficiency scores (combined reading, writing, oral production, listening comprehension) and compared the groups on the early L1 measures and MLAT. Results showed significant differences among the three groups on the L1 achievement measures from 2nd to 5th grades and the MLAT. On all L1 measures, the high-achieving group exhibited significantly stronger L1 skills (and L2 aptitude) than the average- and low-achieving L2 learners as early as 2nd grade. The findings showed that L1 skill differences among secondary L2 learners emerged early in elementary school and were related to L2 proficiency and achievement differences several years later in high school. In another study described earlier, they found that L1 word decoding and L1 spelling skills in elementary school explained over 50% of the variance in L2 word decoding and L2 spelling skills in high school.

In a recent study, 262 U.S. students were followed from 8th grade through two years of Spanish courses in 9th and 10th grades, and 51 of the students were followed through a third-year Spanish course (Sparks, Patton, & Luebbers, Reference Sparks, Patton and Luebbers2019a). For this study, the test battery included L1 skill measures and the MLAT administered in 8th grade as well as L1 cognitive processing skills (working memory, phonological short-term memory, metacognitive knowledge), L1 print exposure, L1 reading attitudes, L1 language analysis measures, and standardized measures of Spanish word decoding, reading comprehension, spelling, vocabulary, writing, and listening comprehension. The participants were divided into high-, average-, and low-achieving groups according to their scores on each of the six measures of Spanish achievement. At the end of the first- and second-year Spanish courses, findings showed significant overall group differences on most L1 achievement tests, all L1 cognitive processing measures, L1 print exposure, L1 language analysis, and L2 aptitude, in which the high-achieving group scored significantly higher than the other groups on all measures. There were significant between-group differences between the high vs. low-achieving groups on all L1 measures, and significant differences between the high vs. average and average vs. low groups on most L1 measures. Because the number of participants who enrolled in and completed third-year Spanish was small, the authors compared the 212 students who had completed the first- and second-year courses with the 51 students who had completed three years of Spanish on all measures. The results showed significant between-group differences on several of the L1 measures (word decoding, working memory, reading comprehension, writing, reading attitudes), the MLAT, and all six L2 achievement tests. A discriminant analysis procedure revealed that four measures best discriminated the two groups: L1 word decoding fluency, L1 reading comprehension, L1 working memory, and the MLAT. Other researchers have also reported findings supporting the claim of L1–L2 cross-linguistic transfer in French (Crombie, Reference Crombie1997), Chinese and English (Chung & Ho, Reference Chung and Ho2010), Finnish and English (Dufva & Voeten, Reference Dufva and Voeten1999), Hebrew and English (Kahn-Horwitz, Shimron, & Sparks, Reference Kahn-Horwitz, Shimron and Sparks2006), and Hungarian and Romanian (Gál & Orbán, Reference Gál and Orbán2013).

Several findings from the aforementioned investigations supported long-term, cross-linguistic transfer of L1–L2 skills. First, students’ early L1 skills played a role in IDs for L2 learning several years after they had mastered their L1. Second, the results showed that students’ L1 skills reflect their L2 achievement in the same skills, that is, students with lower L1 decoding, comprehension, vocabulary, and writing also achieved lower L2 word decoding, comprehension, vocabulary, and writing. Third, L1 and L2 learning may depend on basic language learning mechanics, especially the skills necessary for literacy. Fourth, there were strong correlations between L1 (English) and L2 (Spanish, French, German) literacy skills with more and less orthographic distance. Fourth, students with lower levels of L1 skills exhibited lower levels of L2 aptitude on the MLAT, which measures the language skills necessary to master L2s. Fifth, early L1 skills were strongly related to L2 proficiency and achievement several years after development and mastery of the L1. Sixth, findings that group differences existed in early L1 skills and L2 aptitude and that both early L1 skills and L2 aptitude discriminated between first-/second-year L2 learners vs. third-year L2 learners provided evidence that early L1 skills are strongly related to later L2 achievement.

Are There Relationships between Learning to Read L1 and L2 Alphabetic Orthographies?

The LCDH posits that the primary causal factors for L2 learning are linguistic and that there are strong relationships between students’ L1 ability and their L2 achievement. Sparks et al. have used this basic premise of their model to pursue a line of research related to the relationship between literacy in L1 and L2. Reading is a language-based skill that depends on the linguistic processes and knowledge initially developed for listening and speaking (Petscher et al., Reference Petscher, Cabell and Catts2020). The primary difference between spoken and written language is that for reading, children must extract meaning from print; for writing, they must write (spell) words to convey meaning. Although alphabetic writing systems vary in orthographic depth (i.e., shallow vs. deep orthographies), children must learn that spoken words are comprised of speech sounds (phonemes) and that letters correspond to these sounds. The idea that written symbols are associated with sounds, that is, the alphabetic principle, is the key lesson that children must learn to master word decoding. Once they learn to decode words, children can then make use of linguistic processes and knowledge to comprehend meaning. Skilled readers are generally those who have learned the alphabetic principle for reading (and spelling), while less skilled readers have difficulty with the skills necessary to read (and write) the language. In their volume that addresses reading development across languages and orthographies, Verhoeven and Perfetti (Reference Verhoeven and Perfetti2017) show that there are underlying universals of word reading, all of which require “sensitivity to the specific mapping of linguistic forms onto meaning. Awareness of both phonology and morphology is thus needed to learn how one’s writing system encodes one’s language” (p. 458). These authors note the assumption that reading is based on language appears to be universally shared.

In L1 reading research, the Simple View of Reading (SVR) model (Gough & Tunmer, Reference Gough and Tunmer1986; Hoover & Gough, Reference Hoover and Gough1990; Hoover & Tunmer, Reference Hoover and Tunmer2021) has widespread acceptance as both a theoretical and practical model for predicting students’ reading skills and teaching them to read. The SVR proposes that reading is the product of word decoding and oral language (listening) comprehension. Word decoding depends on efficient, accurate, and automatic retrieval of the phonological and orthographic codes for written words and is essential for reading comprehension. Language comprehension represents the linguistic processes used in the comprehension of oral language, for example, verbal ability, vocabulary, syntax, and inferences. The SVR posits that word decoding and language comprehension make independent contributions to reading skills. In L1 reading, there is voluminous evidence supporting the SVR model (Kilpatrick, Reference Kilpatrick2015, pp. 46–79, 118–119; Seidenberg, Reference Seidenberg2017, pp. 201–203), and findings have shown that decoding and listening comprehension explain most of the variance in reading comprehension skill (Hoover & Tunmer, Reference Hoover and Tunmer2020; Kim, Reference Kim2017). Researchers investigating the model have found that word decoding skill explains more variance in the early stages of learning to read, whereas the contribution of language comprehension increases in later grades (e.g., see Francis et al., Reference Francis, Fletcher, Catts, Tomblin, Paris and Stahl2005). Figure 11.5 depicts the SVR model.

Figure 11.5 Simple View of Reading (SVR) model

Koda (Reference Francis, Fletcher, Catts, Tomblin, Paris and Stahl2005) has suggested that the SVR can be a viable model to explain L2 reading, and recent research supports her view. Gottardo and Mueller (Reference Gottardo and Mueller2009) found that the model explains reading comprehension development in young ELL children, that is, both English oral language proficiency and word decoding are necessary for English reading comprehension. Proctor et al. (Reference Proctor, Carla, August and Snow2005) tested the SVR model with native Spanish speakers and found that English word-level reading skills were related to English reading comprehension, and also that English listening comprehension and English vocabulary were significantly and independently related to English reading comprehension. Droop and Verhoeven (Reference Droop and Verhoeven2003) found that both word decoding and oral language comprehension contributed to reading comprehension with Turkish students learning Dutch. Verhoeven and van Leeuwe (Reference Verhoeven and van Leeuwe2012) reported that the reading comprehension skills of both L1 and L2 learners can be predicted from their language (listening) comprehension and word decoding abilities. They also reported that the power of L2 word decoding to predict L2 reading comprehension diminishes over time, while the influence of L2 language comprehension increases.

Gough and Tunmer (Reference Gough and Tunmer1986) hypothesized that the SVR model has practical implications for the types of readers encountered by classroom teachers. The SVR posits that since reading skills can result only from the product of word decoding and language comprehension, there will be four types of readers. Good readers exhibit both good (average to above average) word decoding and good (average to above average) language comprehension. There will be three different types of poor readers: those with an inability to decode (dyslexia), inability to comprehend (hyperlexia), or inability to both decode and comprehend (mixed). Dyslexic readers have good (oral) language comprehension but exhibit a deficit in word decoding. Hyperlexic readers have strong word decoding accompanied by deficits in language comprehension. Mixed poor readers exhibit both poor word decoding and poor oral language comprehension skills. In L1 reading research, most good readers tend to be good comprehenders, and most poor decoders tend to be poor comprehenders, but the existence of hyperlexic readers shows that good decoding may not always be accompanied by good language comprehension. Likewise, the existence of dyslexic readers shows that good language comprehension may not always be accompanied by good word decoding. Studies over several years have validated the types of reader profiles proposed by the SVR model (e.g., see Catts, Reference Catts2018; Catts, Adolf, & Weismer, Reference Catts, Adlof and Weismer2006).

In contrast to many other countries, the U.S.A. is largely a monolingual society. Most students live in a home where the target L2 is not spoken, and they rarely encounter an L2 in social or academic contexts, except for the L2 classroom. L2 courses generally begin in 9th grade, and students are enrolled with the goal of meeting a graduation requirement, not to become fluent or literate in the language. The U.S. social context for L2 learning is problematic for several reasons, the most prominent being that U.S. students are learning to speak and comprehend the L2 at the same time as they are learning to read and write the L2, in 9th grade, in the absence of L2 vocabulary knowledge.

Given these contextual restraints, Sparks was interested in whether U.S. L2 learners would fit the types of readers proposed by the SVR model and whether language skills would explain the bulk of the variance in L2 reading comprehension. In his first study (Sparks, Reference Sparks2015), 165 high school students completing first- and second-year Spanish courses were administered tests of Spanish word decoding, vocabulary, and reading comprehension from the Batería-III Woodcock-Muñoz (Woodcock et al., 2004, Reference Woodcock, Muñoz-Sandoval, McGrew and Mather2007), a standardized achievement measure normed with native Spanish speakers. The findings showed that the majority (96%) of students fit the hyperlexic poor reader profile (good word decoding, poor reading comprehension) while 4% met the mixed poor reader profile (poor decoding, poor comprehension) when compared to same-age native Spanish speakers; however, no students fit the good or dyslexic reader profiles. All students displayed very low levels of Spanish vocabulary knowledge. In another study with this group, multiple regression analyses showed that Spanish word decoding and Spanish (oral) language comprehension explained 66% of the variance in Spanish reading comprehension, while Spanish vocabulary knowledge explained an additional 3% unique variance (Sparks & Patton, Reference Sparks and Patton2016). As predicted by the authors of the SVR, word decoding and oral language comprehension made separate, independent contributions to reading ability.

Sparks et al. conducted two additional studies with a random sample of U.S. L2 learners, whom they followed over three years of Spanish courses in high school. The students were administered measures from the Woodcock-Muñoz at the end of each year’s course that included Spanish word decoding, Spanish reading comprehension, and Spanish vocabulary. They were then classified into the reader types proposed by the SVR model. In the first study, results showed that 76%–98% of the students were classified as hyperlexic poor readers and that 4%–24% were classified as mixed poor readers at the end of first-, second-, and third-year Spanish courses (Sparks & Luebbers, Reference Sparks and Luebbers2018). No students fit the dyslexic profile (poor decoding, good comprehension), and only 14% fit the good reader profile but not until they were compared to much younger 2nd grade (7-year-old) native Spanish speakers. In a second study with these students, Sparks, Patton, and Luebbers (Reference Sparks, Patton and Luebbers2018b) performed a path analysis procedure and found that Spanish word decoding and oral language comprehension were the strongest predictors of Spanish reading comprehension, but Spanish vocabulary also contributed unique variance to Spanish reading ability. Spanish word decoding and Spanish reading comprehension made independent contributions to Spanish reading ability. U.S. students developed Spanish word decoding skills with relative ease in first-year Spanish but continued to exhibit severe difficulties in L2 reading comprehension and oral language (listening) comprehension, even by the end of third-year Spanish, because of their poor Spanish vocabulary and linguistic knowledge.

The aforementioned results were consistent with the premises of the SVR model and the LCDH. Regarding the SVR, the results supported the propositions that: a) U.S. readers studying Spanish would display variability in their reading profiles consistent with those proposed by the SVR model; b) Spanish word decoding and Spanish oral language comprehension would explain the bulk of variance in Spanish reading comprehension; and c) word decoding and language comprehension would make separate, independent contributions to reading comprehension once a certain level of word decoding in the L2 was attained. A new finding was that L2 oral language comprehension and L2 vocabulary were the limiting factors in proficient L2 reading comprehension. Regarding the LCDH, the results supported the premise that the primary causal factors for L2 reading are linguistic and that there are strong relationships between the skills necessary to read alphabetic orthographies in L1 (English) and L2 (Spanish). In a seminal publication, Sparks (Reference Sparks2021) described how the SVR model can be used to assess the language skills necessary for L2 reading, identify strong and weak L2 readers, and specify L2 readers’ strengths and weaknesses using readily available standardized cognitive and linguistic measures for English and Spanish.

Sparks’ findings have suggested that the question raised by Alderson (Reference Alderson, Alderson and Urquhart1984), Is L2 reading a reading problem or a language problem?, should be revised to ask the following: Is L2 reading a word decoding problem, a language comprehension problem, both a word decoding and language comprehension problem, or neither a decoding nor comprehension problem?